AI Engineer (Edge AI)

Location: Office-based in Bellevue, Washington, United States

Salary: $154,560–$193,200 USD annually, plus equity and subsidized benefits.

Company

hirify.global builds modular AI infrastructure and deployable edge-computing systems for energy, defense, industrial, transportation, and other distributed environments.

What you will do

• Translate operational challenges into AI requirements, datasets, evaluation criteria, and production architectures.
• Design, train, fine-tune, evaluate, and deploy models for vision, language, multimodal AI, time-series analysis, autonomy, and optimization.
• Build datasets and evaluation pipelines from video, images, text, telemetry, sensor, synthetic, and other multimodal data.
• Optimize inference with quantization, pruning, distillation, batching, caching, and hardware-aware acceleration.
• Build containerized AI services and deploy them across Kubernetes, cloud, on-premises, GPU, and disconnected edge environments.
• Develop monitoring, data validation, drift detection, retraining, and controlled-update pipelines while collaborating with customers, product teams, engineers, and domain experts.

Requirements

• Master’s or PhD in applied mathematics, computer science, computational science, engineering, or a related technical field.
• 3+ years of industry experience spanning AI research, machine learning, and production software development.
• Strong Python programming skills and proficiency in Java, C++, or another production language.
• Hands-on experience with statistical machine learning, deep learning, NLP, modern neural architectures, and supervised, unsupervised, transfer, and representation learning.
• Proficiency with PyTorch, TensorFlow, JAX, or comparable deep-learning frameworks.
• Experience deploying models beyond research prototypes, with evidence of technical depth through publications, open-source contributions, or significant production systems.

Nice to have

• Experience with TensorRT, Triton Inference Server, ONNX Runtime, vLLM, CUDA, or similar inference technologies.
• Experience with Kubernetes, microservices, distributed systems, CI/CD, and production MLOps.
• Background in robotics, autonomous systems, industrial, defense, energy, transportation, or safety-critical applications.
• Experience with multimodal systems, synthetic data, active learning, weak supervision, simulation, quantization, pruning, distillation, or LoRA.

Culture & Benefits

• Ownership, autonomy, intellectual curiosity, and a results-oriented approach.
• Competitive base salary with equity.
• Subsidized medical, dental, and vision coverage.
• HSA, FSA, DCFSA, 401(k), and Roth 401(k) options.
• Unlimited paid time off and 14 paid company holidays annually.